Image encryption algorithm based on the finite fields in chaotic maps

Image encryption based on chaotic maps is an important method for ensuring the secure communication of digital multimedia on the Internet. To improve the encryption performance and security of image encryption systems, a new image encryption algorithm is proposed that employs a compound chaotic map and random cyclic shift. First, a new hybrid chaotic system is designed by coupling logistic, ICMIC, Tent, and Chebyshev (HLITC) maps. Comparison tests with previous chaotic maps in terms of chaotic trajectory, Lyapunov exponent, and approximate entropy illustrate that the new hybrid chaotic map has better chaotic performance. Then, the proposed HLITC chaotic system and spiral transformation are used to develop a new chaotic image encryption scheme using the double permutation strategy. The new HLITC chaotic system is used to generate key sequences used in the image scrambling and diffusion stages. The spiral transformation controlled by the chaotic sequence is used to scramble the pixels of the plaintext image, while the XOR operation based on a chaotic map is used for pixel diffusion. Extensive experiments on statistical analysis, key sensitivity, and key space analysis were conducted. Experimental results show that the proposed encryption scheme has good robustness against brute-force attacks, statistical attacks, and differential attacks and is more effective than many existing chaotic image encryption algorithms.

The main purpose of the proposed image encryption (IE) method is to enhance various security characteristics to protect sensitive images on the internet. In the literature, chaotic maps are preferred for image encryption because of their high randomness and sensitivity to initial parameter values. Therefore, metaheuristic algorithms have been utilized to fine-tune the parameters. In this research, we have employed the metaheuristic Lyrebird optimization (LO) algorithm to fine-tune the chaotic map parameters. The LO algorithm is chosen over other algorithms due to its better exploration and exploitation rate to search for the best solution. The LO algorithm searches for the best parameter value based on the objective function. This research involves the formulation of a multi-objective function that incorporates numerous security parameters, namely, entropy and correlation coefficient (CC), to improve the security attributes of the IE model. The proposed IE model has two steps. In the first step, a random key is generated to transform the pixels of the secret image, whereas in the second step, the image pixels are shuffled based on the shuffling index values to reduce the correlation among the neighboring pixels. In both steps, we have used the chaotic logistic map. The proposed IE is evaluated against statistical and differential attacks on the standard dataset by considering the various images and their different resolutions. The uniform distribution of the histogram of the encrypted images is validated using the chi-square test. Besides that, entropy analysis shows that the average entropy value is 7.9973, 7.9993, and 7.9998 for 256x256, 512x512, and 1024x1024 image resolutions. The average CC and SSIM are near zero value. The average NPCR value (>0.9969) is near the 1 value. Finally, the comparative analysis based on entropy, CC, and NPCR parameters shows that the proposed IE model outperforms the existing models.

Recently, due to the initial sensitivity, ergodicity, boundedness, and unpredictability of chaos, it has been widely used in the fields of secure communication, signal processing, chaotic synchronization, etc. Moreover, due to the low complexity of hardware implementation, widespread attention to one-dimensional (1D) chaotic maps has been paid from researchers. However, some existing 1D maps have simple chaotic behaviors and discrete chaotic intervals, which have significantly affected the practical application. To address these shortcomings, this paper proposes a 1D chaotic model based on the absolute value function and the cosine function called the cosine-coupled chaotic model (CCCM). It can use existing 1D chaotic maps as seed maps to construct a series of 1D chaotic maps with continuous chaotic intervals and complex chaotic behaviors. To verify the effectiveness of the CCCM, we first generate three new chaotic maps using the CCCM, and then their chaotic properties are analyzed by using various measures including Lyapunov exponent (LE), sample entropy (SE), correlation dimension (CD), 0-1 test and sensitivity. The experimental results confirm that the new chaotic maps have wider chaotic intervals and more complex chaotic behaviors than the corresponding seed maps and some other advanced chaotic maps. Then we use a field programmable gate array (FPGA) as the hardware platform for simple hardware implementations of the new chaotic maps. And a new pseudo-random number generator (PRNG) is introduced to verify practical applications of the new maps. Finally, experimental results show that the new chaotic maps can be implemented on FPGA and the proposed PRNG has strong random properties.

RGB image encryption based on symmetric keys using Arnold transform, 3D chaotic map and affine hill cipher

This paper puts forward a novel image encryption algorithm that is based on permutation-diffusion architecture. In pixels' permutation stage, algorithm takes full advantage of the idea of magic cube's scrambling. There is only simple cyclic shift operation in each sub-block's permutation, but when the algorithm has disposed the current sub-block, the adjacent sub-blocks will be dealt with, too. In the cyclic shift of each row, stable points will help to decrease the correlation of adjacent pixels. To make encryption procedure uncertain, this paper brings in a parameter named delay-time that is generated by chaotic map. In the diffusion stage, by combining multiple operations and dynamic look-up table together, the proposed algorithm highly increases the uncertainty of the encryption procedure. At last, the experiment results of key space analysis, information entropy analysis, histogram analysis and etc. show that the encryption algorithm has well performance and it can be used in image encryption and transmission.

Exponentially increasing multimedia data over the internet raises concerns over its security. In the current work, we present a new technique for encrypting digital images based upon the pixel shuffling combined with changing pixel values using 128-bit secret key using henon chaotic map. Chaotic maps are characterized by their high sensitivity towards the initial parameters, which makes it a natural choice for developing a dynamic permutation matrix or as it is mostly called, permutation map. So we used chaotic Henon map in order to dynamically generate the permutation matrix. The initial parameters of the chaotic map and the secret key for changing the pixel values are derived from an external secret key. Horizontal and vertical permutations are used to perform pixel shuffling. Shuffling is used to destroy the correlation among the neighbour or adjacent image pixels, also it helps in increasing diffusion in the image. The proposed scheme is tested against a series of tests to measure its performance. Results of such tests indicate that the proposed algorithm is highly sensitive towards the encryption key and showed high resistance against various brute-force or statistical attacks.

The paper introduces an efficient asymmetric algorithm for encrypting images utilizing chaotic maps and elliptic curve cryptography. In the proposed image encryption method, there is a combination of elliptic curve ElGamal encryption method with masking of image through chaotic map for enhancing security and efficiency. The proposed algorithm can encrypt images of any size. Security analysis is carried through to validate efficiency, sturdiness and feasibility of the algorithm. Compare to recent related encryption schemes, this scheme has better ability to resist crypt analytical and statistical attacks.

This paper introduces a novel parameter-control framework to produce many new one-dimensional (1D) chaotic maps. It has a simple structure and consists of two 1D chaotic maps, in which one is used as a seed map while the other acts as a control map that controls the parameter of the seed map. Examples and analysis results show that these newly generated chaotic maps have more complex structures and better chaos performance than their corresponding seed and control maps.

In this paper, a chaotic image encryption algorithm is suggested combining with double chaotic maps, SHA‐3 (Secure Hash Algorithm‐3), and auto‐updating system. To shuffle pixel positions, a matrix having same size of the plain‐image is generated dependent on the plain‐image in stage of permutation. Then, SHA‐3 is taken to calculate its hash values used to produce control parameter and initial condition of Logistic map. After that, total permutation is implemented for row and column to exchange pixels, where auto‐updating systems are established by different images acting like one‐time pad. Furthermore, 3D chaotic cat map is employed to enlarge key space in diffusion process. Permuted image is firstly divided into four sub‐blocks, which are queued randomly according to the key of Logistic map. The last sub‐block is picked out to calculate the hash values using SHA‐3, of which are assigned into three groups to update the initial conditions of 3D chaotic cat map performing like one‐time pad again. Current sub‐block is designed to influence next sub‐block in diffusion process. As a result, the proposed algorithm can resist efficiently the chosen‐plaintext and known‐plaintext attacks. Experimental results are also given to explain the high security of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

In the last decade, the communication of images through the internet has increased. Due to the growing demands for data transfer through images, protection of data and safe communication is very important. For this purpose, many encryption techniques have been designed and developed. New and secured encryption schemes based on chaos theory have introduced methods for secure as well as fast communication. A modified image encryption process is proposed in this work with chaotic maps and orthogonal matrix in Hill cipher. Image encryption involves three phases. In the first phase, a chaotic Henon map is used for permuting the digital image. In the second phase, a Hill cipher is used whose encryption key is generated by an orthogonal matrix which further is produced from the equation of the plane. In the third phase, a sequence is generated by a chaotic tent map which is later XORed. Chaotic maps play an important role in the encryption process. To deal with the issues of fast and highly secured image processing, the prominent properties of non-periodical movement and non-convergence of chaotic theory play an important role. The proposed scheme is resistant to different attacks on the cipher image. Different tests have been applied to evaluate the proposed technique. The results of the tests such as key space analysis, key sensitivity analysis, and information entropy, histogram correlation of the adjacent pixels, number of pixel change rate (NPCR), peak signal to noise ratio (PSNR), and unified average changing intensity (UCAI) showed that our proposed scheme is an efficient encryption technique. The proposed approach is also compared with some state-of-the-art image encryption techniques. In the view of statistical analysis, we claim that our proposed encryption algorithm is secured.

A novel compression-based 2D-chaotic sine map for enhancing privacy and security of biometric identification systems

A modern method for gray image enciphering depends on two techniques which are; DNA Exclusive-OR operation and 2D Chaotic Map is introduced. In preprocessing level, Arnold Transform is first applied on plain gray image for shuffling. Then, a DNA 2D matrix is resulted from encoding the shuffled gray image. Next, each of Henon Map and Ikeda Map are employed in keys generation to be used in the substitution and permutation process, respectively. The last process is decoding the resulted 2D matrix, and the enciphered image is obtained. The introduced method can acquire fine enciphering effect; has very low correlation (correlation close to zero), as well attains satisfactory entropy value close to 8, a wide secret key's space, strong sensitivity to secret key was the NPCR over 99% and UACI up to 33%, and has the abilities of resisting exhaustive attack and statistic attack as the investigational outcome and security analysis showed.

This work utilizes a novel image encryption technique for block image encryption with the help of nonlinear 2D chaotic map and DNA sequences (NL2DCM-DNA). 2D chaotic map has generated the several key sequences for encryption, and DNA rules are applied to perform fast block encryption of image. Nonlinearity of 2D chaotic map and complexity of DNA sequences are used to perform highly secure image encryption. The experimental outputs illustrate the higher efficiency of NL2DCM-DNA in terms of security, attack resilience, entropy, histogram, running time and diffusion against some previous image encryption algorithms.

This paper presents a permutation-diffusion architecture based symmetric color image encryption scheme. In the permutation stage, the three color components of a color image are shuffled separately by using Arnold cat map, so as to eliminate the strong correlation among adjacent pixels. Then in the diffusion stage, the shuffled R, G, B components are masked by three pseudo-randomness key streams quantified from Chen's chaotic system, respectively, with the purpose of confusing the relationship between the cipher image and plain image. Thorough security tests are carried out with detailed analysis, including the most important ones like key space analysis, statistical analysis and key sensitivity analysis, which has demonstrated the satisfactory security of the proposed scheme.

New method for fingerprint images encryption using DNA sequence and chaotic tent map